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Social Analytics (COMP90076)
Graduate courseworkPoints: 12.5Not available in 2019
Overview
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Social networks and social platforms are a widely used technology for connecting individuals and connecting organisations. They can provide key insights into human and organizational behaviours and needs. This subject will introduce students to methods for analyzing data generated by social networks and social platforms.
The following topics will be covered: network structure and semantics, including friend‐follower relationships; social network analysis fundamentals including connectedness, centrality and influence; community detection; social network visualisation methods; combining text and social network analysis; user modelling, including prediction and recommendation strategies; gaining insights into groups of users via clustering/segmentation; trend monitoring in social networks; prediction and anomaly detection in networks; automated social interaction: conversational chatbots and their inferential capabilities and interfaces; case studies in public health surveillance, education and psychology.
Intended learning outcomes
On completion of this subject, students should be able to:
- Evaluate and apply key techniques used in social analytics and deploy them in combination for different scenarios
- Critique component technologies in commonly deployed systems that analyse social networks and be able to communicate issues relevant to the effective implementation and operation of such systems
- Explain and justify to others the use of social network analysis algorithms for real world use by individuals or organisations
Generic skills
Students will be provided with the opportunity to practice and reinforce:
- High level written communication skills
- Advanced information and interpretation skills
- Advanced analytic, integration and problem‐solving skills
- Demonstrate competence in critical and theoretical thinking through report writing and online discussions
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST90130 | Critical Thinking with Analytics |
Term 3 (Online)
Term 1 (Online)
|
12.5 |
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 3 November 2022
Assessment
Description | Timing | Percentage |
---|---|---|
Problem solving
| Week 3 | 25% |
Case study proposal/discussion
| Week 6 | 25% |
Project
| Week 8 | 40% |
Participation in online discussions
| Week 8 | 10% |
Last updated: 3 November 2022
Dates & times
Not available in 2019
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
Students will have access to electronic copies of relevant readings
- Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Last updated: 3 November 2022